
Sr. Data Scientist
- USA
- Permanent
- Full-time
- Design, develop, test, and maintain scalable software systems that enable data science workflows, including data ingestion, transformation, feature engineering, and model deployment.
- Collaborate cross-functionally with data scientists, machine learning engineers, product managers, and other software engineers to integrate intelligent solutions into production environments.
- Build and optimize data pipelines, Application Programming Interfaces (APIs), and tools that support experimentation, automation, and reproducibility in machine learning development.
- Ensure software quality, security, and compliance through robust testing, code reviews, and adherence to engineering best practices.
- Leverage telemetry and logging to monitor system health, debug issues, and improve performance.
- Contribute to architectural decisions and long-term technical strategy for data-driven applications.
- Stay current with emerging technologies and best practices in software engineering, data science, and machine learning infrastructure.
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results.
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results
- OR equivalent experience.
- 3+ years proficiency in at least one programming language such as Python, C#, Java, or C++.
- 4+ years of professional software development experience, including designing, building, and maintaining production-quality systems.
- 3+ years of experience working with data systems, including relational databases, distributed data processing frameworks (e.g., Spark, Hadoop), or modern data warehouses.
- 1+ year(s) understanding of software engineering fundamentals, including data structures, algorithms, and system design.
- 1+ year(s) of demonstrated ability to collaborate effectively with cross-functional teams.
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
- 1+ year(s) of experience building or supporting machine learning systems or data science workflows in production environments.
- 1+ year(s) of familiarity with data science and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, MLflow).
- 1+ year(s) working knowledge of cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP), especially with data and machine learning (ML) services (e.g., Azure Data Factory, AWS SageMaker, Google Vertex Artificial Intelligence (AI)).
- 1+ year(s) of experience with continuous integration and continuous delivery (CI/CD) pipelines and development and operations (DevOps) practices for data-driven applications.